Indirect System Condition Monitoring Using Online Bayesian Changepoint Detection

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

This paper presents a method for online vibration analysis and a simple test bench analogue for the solder pumping system in an industrial wave-soldering machine at a Siemens factory. A common machine fault is caused by solder build-up within the pipes of the machine. This leads to a pressure drop in the system, which is replicated in the test bench by restricting the flow of water using a gate valve. The pump’s vibrational response is recorded using an accelerometer. The captured data is passed through an online Bayesian Changepoint Detection algorithm, adapted from existing literature, to detect the point at which the change in flow rate affects the pump, and thus the PCB assembly capability of the machine. This information can be used to trigger machine maintenance operations, or to isolate the vibrational response indicative of the machine fault.

Details

Original languageEnglish
Title of host publicationSmart Technologies for Precision Assembly - 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, Revised Selected Papers
EditorsSvetan Ratchev
Pages81-92
Number of pages12
Publication statusPublished - 2 Apr 2021
Peer-reviewedYes

Publication series

SeriesSmart Technologies for Precision Assembly
Volume620
ISSN1868-4238

External IDs

Scopus 85107427436
ORCID /0000-0001-6734-704X/work/142235738

Keywords

Keywords

  • Bayesian changepoint detection, Industrial application, Predictive maintenance